Systematic Review of Patient-specific Instrumentation in Total Knee Arthroplasty: New but Not Improved
Bibliographic record
Abstract
BACKGROUND: Patient-specific cutting blocks have been touted as a more efficient and reliable means of achieving neutral mechanical alignment during TKA with the proposed downstream effect of improved clinical outcomes. However, it is not clear to what degree published studies support these assumptions. QUESTIONS/PURPOSES: We asked: (1) Do patient-specific cutting blocks achieve neutral mechanical alignment more reliably during TKA when compared with conventional methods? (2) Does patient-specific instrumentation (PSI) provide financial benefit through improved surgical efficiency? (3) Does the use of patient-specific cutting blocks translate to improved clinical results after TKA when compared with conventional instrumentation? METHODS: We performed a systematic review in accordance with Cochrane guidelines of controlled studies (prospective and retrospective) in MEDLINE® and EMBASE® with respect to patient-specific cutting blocks and their effect on alignment, cost, operative time, clinical outcome scores, complications, and survivorship. Sixteen studies (Level I-III on the levels of evidence rubric) were identified and used in addressing the first question, 13 (Level I-III) for the second question, and two (Level III) for the third question. Qualitative assessment of the selected Level I studies was performed using the modified Jadad score; Level II and III studies were rated based on the Newcastle-Ottawa scoring system. RESULTS: The majority of studies did not show an improvement in overall limb alignment when PSI was compared with standard instrumentation. Mixed results were seen across studies with regard to the prevalence of alignment outliers when PSI was compared with conventional cutting blocks with some studies demonstrating no difference, some showing an improvement with PSI, and a single study showing worse results with PSI. The studies demonstrated mixed results regarding the influence of PSI on operative times. Decreased operative times were not uniformly observed, and when noted, they were found to be of minimal clinical or financial significance. PSI did reliably reduce the number of instrument trays required for processing perioperatively. The accuracy of the preoperative plan, generated by the PSI manufacturers, was found lacking, often leading to multiple intraoperative changes, thereby disrupting the flow of the operation and negatively impacting efficiency. Limited data exist with regard to the effect of PSI on postoperative function, improvement in pain, and patient satisfaction. Neither of the two studies we identified provided strong evidence to support an advantage favoring the use of PSI. No identified studies addressed survivorship of components placed with PSI compared with those placed with standard instrumentation. CONCLUSIONS: PSI for TKA has not reliably demonstrated improvement of postoperative limb or component alignment when compared with standard instrumentation. Although decisive evidence exists to support that PSI requires fewer surgical trays, PSI has not clearly been shown to improve overall surgical efficiency or the cost-effectiveness of TKA. Mid- and long-term data regarding PSI's effect on functional outcomes and component survivorship do not exist and short-term data are scarce. Limited available literature does not clearly support any improvement of postoperative pain, activity, function, or ROM when PSI is compared with traditional instrumentation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.107 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.009 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".